Abstract

Electronic marketplaces have been booming in the past decade. Many of them (e.g., Amazon, Apple App Store and Google Play) create an almost zero barrier-to-entry en- vironment, facilitating independent authors, programmers and artists to list their books, software and songs respec- tively for sale. However, existing literature supports the hypothesis that promoting a product has a strong effect on sales. As a result, many of the users that participate in these environments collaborate with promoting agencies, such as publishers, software companies and music labels. Hence, even though these markets create an outlet for independent pro- fessionals to rise, broker-style third-party companies might create an invisible barrier for them. In this work, we study the effect of these promoting agents on the placement of a song on the charts. By collecting and analyzing a unique dataset from a major marketplace of electronic music we first deploy an Accelerated Failure Time survival model to estimate the probability of a song to appear on the charts. Next, we employ a multidimensional tree-based causal infer- ence approach and we identify how the interplay of different music label’s characteristics (treatment) affect the placement of a song. Our results indicate that certain combinations of treatments increase a song’s probability to get in the charts by a factor of six. Our work provides insights (i) on the importance of promoting agents in these marketplaces, as well as (ii) on potential actionable ways for overcoming the invisible barrier that could pave the way for independent artists to succeed.